New work looking at genetic risk and the links with inflammatory disease and COVID-19 will not only help predict those patients at more severe risk of Covid, but also provide a pathway for use in different clinical settings to improve patient care and ultimately save and extend lives.

The first part of the work, looking at polygenic risk scores and their connection to COVID-19 is a collaboration between Dr Mark Iles, from the Leeds Institute of Medical Research (LIMR), and Prof Ann Morgan Head of the Molecular and Personalised Medicine Group within the Leeds Institute of Cardiovascular and Metabolic Medicine (LICAM) supported by PhD student, Natalie Chaddock. Dr Iles’ work includes design and analysis of population-based genetic epidemiology studies and the theoretical statistics and methodology underlying them, and Prof. Morgan has a keen interest in co-morbidities and their impact on specific types of illness. The aim of this particular project was to identify clinical, socio-demographic and genetic risk factors for severe COVID-19 in the general population. Severe cases were those which included hospitalization, critical care admission or death.

Polygenic risk scores represent the total number of genetic variants that an individual has and helps to assess their heritable risk of developing a particular disease. The team used 9560 UK Biobank participants diagnosed with COVID-19 during 2020 to identify scores for COVID-19, from a COVID-19 dataset. “We can learn more about the pathogenesis of the virus,” says Dr Iles. “Polygenic risk scores can reveal someone to be at high risk if they were to contract COVID-19, because of them having a tendency to develop a certain disease shown by the genetic predictors. Even if they don’t actually have the disease – perhaps because they’re not yet old enough to develop it, or because of lifestyle factors – their risk of getting severe COVID-19, involving hospitalisation in intensive care and possibly dying, is still there.” But the impact goes further. “Through this work, more can be discovered about the biological pathways leading to other diseases.” adds Natalie.

A second project, undertaken by the team is looking at using polygenic risk scores for biomarker traits relating to body composition, such as BMI and body fat percentage, in connection with peripheral vascular disease.

This work could eventually lead to everyone being routinely tested for polygenic risk scores for developing all diseases. Genetic testing is becoming cheaper to deploy, making it more realistic to use in clinical practice. Individually, the high-risk variant markers identified through polygenic risk scores do not have a big impact, but the more of them a patient is carrying, the greater the risk they have.

“Rather than testing for one particular disease, we are able to look at the whole genome,” says Dr Iles. “People can be stratified in terms of risk for anything and prioritised for screening. Those at higher risk would be screened earlier, those at low risk later. So for example in breast cancer, we could catch it sooner, without having to increase spending on doing more screening. This would improve patient care, save and extend lives, and save money for the NHS too.”

The work has already led to a new project, Our Future Health, recruiting patients in Leeds Chapel Allerton Hospital and using polygenic risk scores in a clinical setting to improve diagnosis and predict who will get side effects. “With rheumatoid arthritis (RA), for example, the current system involves trying one drug and seeing if the patient has side effects; if so, then we move on to another drug and see if there are any side effects to that,” explains Dr Iles. “The problem is, RA is a progressive disease. We can’t turn that round and reverse it when the right drug is found. With polygenic testing, we can find the right drug earlier, leading to happier, healthier patients.”

About Dr Mark Iles: https://medicinehealth.leeds.ac.uk/medicine/staff/463/dr-mark-iles

About Prof Ann Morgan: https://medicinehealth.leeds.ac.uk/medicine/staff/2614/professor-ann-morgan

Mar Pujades-Rodriguez, Senior Consultant Epidemiologist for EMEA Data Science has also been involved in this project.

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